IEEE

Solving Ordinary Differential Equations With Adaptive Differential Evolution

Abstract: Solving ordinary differential equations (ODEs) is vital in diverse fields. However, it is difficult to obtain the exact analytical solutions of ODEs due to their changeable mathematical ...
IEEE

A Fast-Convergence Near-Memory-Computing Accelerator for Solving Partial Differential Equations

Abstract: Solving partial differential equations (PDEs) is omnipresent in scientific research and engineering and requires expensive numerical iteration for memory and computation. The primary ...
GitHub

zwicker-group/py-pde

py-pde is a Python package for solving partial differential equations (PDEs). The package provides classes for grids on which scalar and tensor fields can be defined. The associated differential ...
GitHub

Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity

The data and code for the paper H. Zhang, L. Liu, K. Weng, & L. Lu. Federated scientific machine learning for approximating functions and solving differential equations with data heterogeneity. IEEE ...
Frontiers

Implementing physics-informed neural networks with deep learning for differential equations

Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...